Job Overview
Location
Remote
Job Type
Full-time
Category
Software Engineering
Date Posted
May 22, 2026
Full Job Description
đź“‹ Description
- • Design and execute fine-tuning strategies for structured generation and editing workflows using open-source language models such as Llama, Qwen, Mistral, and DeepSeek.
- • Build supervised datasets from production-generated outputs, user edits, retries, and failures to improve model performance and output quality.
- • Develop measurable benchmarks for generation quality, correctness, consistency, and runtime performance, moving beyond subjective review to data-driven evaluation.
- • Implement LoRA, QLoRA, supervised fine-tuning (SFT), distillation, preference tuning, and synthetic data generation techniques to optimize model behavior for creative workflows.
- • Construct automated pipelines for collecting, cleaning, evaluating, and promoting production interaction data into training datasets.
- • Use validation systems, intermediate representations, runtime analysis, and rendered outputs as structured feedback signals to guide model improvements.
- • Improve retry, repair, and self-correction workflows within AI generation pipelines to enhance reliability and user experience.
- • Engineer natural-language-to-structured-content generation systems that preserve structural integrity and domain-specific constraints.
- • Build structure-preserving editing and modification systems that enable precise AI-assisted changes to animated, graphical, or design-oriented content.
- • Develop evaluation and observability pipelines to monitor generation quality, model drift, and system performance in real-world usage.
- • Create smaller, lower-latency models tailored for targeted tasks such as generation, editing, routing, and repair in creative tooling environments.
- • Design multi-step orchestration and self-correction workflows that enable AI systems to iteratively refine outputs based on feedback signals.
- • Collaborate cross-functionally with engineering, design, and product teams to align AI system improvements with user needs and product goals.
- • Debug complex systems spanning model outputs, validation logic, runtime behavior, and rendered results to identify root causes of failure or degradation.
- • Define and implement objective evaluation criteria for structured outputs, ensuring consistency, correctness, and usability in production.
- • Work with production usage and interaction traces to iteratively refine training data and model behavior for real-world creative workflows.
- • Focus on production-grade AI infrastructure that prioritizes model reliability, scalability, and integration into user-facing creative tools.
🎯 Requirements
- • Strong experience building with LLMs or structured generation systems in production or applied research settings
- • Hands-on experience fine-tuning or adapting open-source language models
- • Strong Python engineering skills
- • Experience building evaluation systems, ML experimentation workflows, or data pipelines
- • Strong understanding of prompt engineering, structured outputs, tool use, and model failure analysis
- • Ability to define measurable evaluation criteria rather than relying only on subjective review
🏖️ Benefits
- • Fully remote position
- • Direct hire opportunity
- • Work on real-world AI systems used in creative production workflows
- • Collaborate with a highly technical and product-focused engineering team
- • Tackle challenging problems involving structured generation, multimodal systems, and AI reliability
- • Opportunity to shape production-grade AI systems for next-generation creative tooling
Skills & Technologies
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About G2i Inc.
G2i is a technical talent marketplace that pre-vets React, React Native, and Node.js engineers for U.S. companies. Founded by developers to solve hiring pain, it runs extensive code reviews, pair-programming interviews, and background checks before matching engineers for contract or full-time remote roles. G2i emphasizes mental health, offering a monthly wellness stipend and a zero-burnout policy. The company also provides direct-hire services and manages payroll, compliance, and ongoing support, enabling startups and enterprises to scale engineering teams quickly while maintaining code quality and developer well-being.
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